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#iconohash presents #phdchat

Scroll down for the #phdchat conversation report for May 3rd, 2021 EST.

iconohash

the world's conversation archive

#phdchat for May 3rd, 2021 EST

01
4th

coming together

When it comes to participants, we ranked 4th among 192 conversations.

4th

participating

In terms of the number of posts, we ranked 4th out of 192 conversations that took place.

3rd

amplification

This conversation ranked 3rd out of 192 in terms of the amplification of ideas & content.

how we participated. Here's how participants reacted & engaged each other

Reactions
71%

Amplified

There were 192 reshares, 71% of posts, during the course of the conversation.

1%

Engaged

1% of participants in this conversation engaged each other 3 times.

12%

Content

12% of participants in this conversation shared a total of 7 unique pieces of content.

quick facts.

Here are the basic facts of the conversation for for May 3rd, 2021.

0
Active
Participants
0
Posts
Total

meet the influencers the movers and shakers of #phdchat

02

the top of the list. Top influencers in the chat

IMPACT
@Dr_Meming

@Dr_Meming

Dr Meming
Managed to meme my way through a PhD, but can I do the same during a postdoc? @Dr_Meming for RTs

@DNA_RNA_Uni

@DNA_RNA_Uni

DNA&RNA Universe
...

@Shireenhayati

@Shireenhayati

Shireen Hayat
Public health doctoral student advocating for effective, efficient and equitable healthcare. I am fairly certain health economics is fun! #valueimaging

about the participants. let's take a look at everyone who show'd up

03

top professions what are they doing when they're not in #phdchat

insight

  the top participating professions
out of 34 total

research
academic
professor
manager
writer

gender an estimation of what the gender break down looks like
= 1 men or women

insight

Women

Men

about the content. the best content that was shared

04
Machine learning-based prediction models for accidental hypothermia patients | Journal of Intensive Care | Full Text
Background Accidental hypothermia is a critical condition with high risks of fatal arrhythmia, multiple organ failure, and mortality; however, there is no established model to predict the mortality. The present study aimed to develop and validate machine learning-based models for predicting in-hospital mortality using easily available data at hospital admission among the patients with accidental hypothermia. Method This study was secondary analysis of multi-center retrospective cohort study (J-p

chat growth how is #phdchat growing over time?

05

want more? are you interested in the full data analysis for this chat? Full transcript? Longer view at chat growth?

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